Plant tropisms as a window on plant computational processes

Area of Science:

• Plant Biology
• Computational Biology
• Mathematical Modeling

Background:

• Plants are sessile organisms with remarkable adaptive behaviors crucial for survival in fluctuating environments.
• Lacking a central nervous system, plants utilize distributed systems for complex information processing at the tissue level.

Purpose of the Study:

• To propose plant tropisms as an ideal framework for studying plant computational processes.
• To establish a dialogue between mathematical modeling and biological observations in plant science.
• To infer relationships between tropic responses and stimuli using macroscopic models.

Main Methods:

• Utilizing plant tropisms as a mathematical input-output system.
• Focusing on macroscopic models to describe plant computational processes.
• Analyzing interactions at hierarchical levels: internal state, abiotic environment, and neighboring plants.

Main Results:

• Tropisms provide a robust mathematical description for plant adaptive behaviors.
• Macroscopic models can elucidate computational processes underlying tropic responses.
• Examples demonstrate the application of this framework across different interaction levels.

Conclusions:

• Plant tropisms serve as a powerful model system for understanding plant computation.
• Mathematical modeling of tropisms facilitates the study of plant adaptation and interaction.
• This approach bridges the gap between theoretical models and empirical observations in plant science.